We are a research group at the Department of Immunology, Genetics and Pathology (IGP) at Uppsala University. Our primary research goals are directed towards understanding the complex regulation in cancer cells, ultimately aiming at new therapeutic strategies. Combining mathematical and experimental methods, our lab focuses on cancers of the nervous system. This is a challenging but important area of investigation, where IGP has an excellent unit with complementary expertise. On this page, you will find information about our cross-disciplinary team and projects. You are welcome to contact us for further information.
In this project, we develop systems biology strategies for the targeting of cancer stem cells (CSCs) in individual patients suffering from glioblastoma. CSCs are crucial for the maintenance and progression of these cancers, but the systems-scale characterization of CSCs has so far been limited by the lack of relevant model systems for large-scale functional studies. Our project takes advantage of the Human Glioma Cell Culture—HGCC biobank, a world-unique clinical material that comprises an extensive collection of early-passage glioblastoma CSC cultures derived from more than a hundred consecutive patient cases at Uppsala University Hospital during 2010-2012.
A major challenge in current cancer research is to gain biological insight from large scale molecular data from patient samples. In this project, we invent new mathematical methods to construct regulatory maps of multiple cancer diagnoses. Our system uses data from both public sources and from IGP/SciLifeLab. The results are made available on a new web resource, Cancer Landscapes. A unique feature of Cancer Landscapes is that very complex data become available in an intuitive form, which lab biologists can use to design experiments.
Brain tumors are characterized by invasive growth, which makes surgical resection inefficient. In this project, we develop new mathematical simulations of brain tumor growth to understand the principles of brain tumor invasiveness, and to determine new strategies to inhibit invasive growth. The models should be applicable to designing relevant cell screens for glioblastoma and cytometry-based patient prognostics.
Do you want to conduct a challenging project in state-of-the-art computational biology? Do not hesitate to contact us.